Director Sales Analytics

Job Description

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities

• Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement.
• Designing and building data pipelines to automate data movement and processing.
• Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
• Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
• Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.

Director Expectations

• To manage a business function, providing significant input to function wide strategic initiatives. Contribute to and influence policy and procedures for the function and plan, manage and consult on multiple complex and critical strategic projects, which may be business wide..
• They manage the direction of a large team or sub-function, leading other people managers and embedding a performance culture aligned to the values of the business. Or for an individual contributor, they lead organisation wide projects and act as deep technical expert and thought leader, identifying new ways of working and collaborating cross functionally. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Provide expert advice to senior functional management and committees to influence decisions made outside of own function, offering significant input to function wide strategic initiatives.
• Manage, coordinate and enable resourcing, budgeting and policy creation for a significant sub-function.
• Escalates breaches of policies / procedure appropriately.
• Foster and guide compliance, ensure regulations are observed that relevant processes in place to facilitate adherence.
• Focus on the external environment, regulators, or advocacy groups to both monitor and influence on behalf of Barclays, when appropriate.
• Demonstrate extensive knowledge of how the function integrates with the business division / Group to achieve the overall business objectives.
• Maintain broad and comprehensive knowledge of industry theories and practices within own discipline alongside up-to-date relevant sector / functional knowledge, and insight into external market developments / initiatives.
• Use interpretative thinking and advanced analytical skills to solve problems and design solutions in often complex/ sensitive situations.
• Exercise management authority to make significant decisions and certain strategic decisions or recommendations within own area.
• Negotiate with and influence stakeholders at a senior level both internally and externally.
• Act as principal contact point for key clients and counterparts in other functions/ businesses divisions.
• Mandated as a spokesperson for the function and business division.

All Senior Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Hands-on Sales Analytics leader who turns Markets Sales growth opportunities into production analytics and AI/ML capabilities with clear KPI outcomes, strong governance, and senior stakeholder alignment.

Key role highlights

• Commercial-impact role focused on measurable Sales outcomes (uplift, win-rate, pipeline velocity, wallet share, and coverage productivity).
• Hands-on expectation to code and prototype, contributing production-grade analytics/ML components (not only oversight).
• Own use-case pipeline from idea to scaled adoption, with KPI definition, testing/experimentation, and benefits tracking.
• Build on modern data/ML platforms (e.g., Databricks/Spark and Snowflake) with CI/CD, monitoring, and operational controls.
• Operate in a controlled environment with strong model governance (model risk, compliance, and controls).
• Partner with senior stakeholders across Sales, Product, Risk/Compliance, CDO/CTO, SMAD/Quants, and engineering to secure decisions and deliver outcomes.

Purpose of the role -

As Director - Sales Analytics, you will use data, analytics, and hands-on AI/ML to deliver measurable commercial impact across Markets Sales (e.g., revenue uplift, conversion/win rate, pipeline velocity, wallet-share growth, and coverage productivity). You will build a prioritised pipeline of high-value use cases across the opportunity lifecycle (e.g., targeting, next-best action, and coverage effectiveness) and take them from discovery through deployment and adoption using trusted data, strong model governance, and hands-on engineering. You will lead senior stakeholders across Sales, Product, Risk and Compliance, partnering with CDO/CTO, SMAD/Quants, and engineering/data teams to align priorities, secure decisions, and deliver outcomes.

• Key responsibilities

• Deliver Markets Sales commercial impact with hands-on analytics and AI/ML (uplift, win-rate, pipeline velocity, wallet share, coverage productivity).
• Build a prioritised use-case pipeline (targeting, next-best action, coverage effectiveness) and ship to production with KPI definition and tracking.
• Engineer end-to-end solutions, personally coding/prototyping critical components from data prep and features to modelling, productionisation, monitoring, and support.
• Operationalise analytics/ML with trusted data, model governance, and delivery controls (CI/CD, deployment, monitoring) on Databricks/Spark and Snowflake.
• Lead senior stakeholders (Sales, Product, Risk/Compliance, CDO/CTO, SMAD/Quants, engineering/data) to align priorities, secure decisions, and deliver outcomes.

• Essential candidate skills

• Demonstrated ability to deliver analytics and AI/ML end-to-end, writing production-grade code from problem framing through build, deployment, and adoption.
• Demonstrated ability to engineer trusted data and features (quality, lineage, reusable metrics) using Python/SQL on Databricks/Spark and Snowflake.
• Demonstrated ability to apply engineering discipline to analytics/ML (Git, automated testing, code review, and CI/CD) to ship reliable changes.
• Demonstrated ability to prioritise use cases with clear KPIs and run experiments that evidence commercial impact.
• Demonstrated ability to influence senior stakeholders and deliver at scale within governance (model risk, compliance, and controls).

• Desirable skills (optional) 

• Markets Sales analytics use cases (targeting, next-best action, coverage effectiveness, pipeline) plus market data and pre/post-trade analytics; Kafka and dbt exposure a plus.
• Hands-on coding in Python, SQL, and PySpark for pipelines and production analytics/ML; Java/C++ or kdb+/q a bonus.
• MLOps in a controlled environment: MLflow, registry/versioning, CI/CD (GitLab/Jenkins), drift/performance monitoring, documentation.
• Data governance practices and tooling: data quality checks, lineage/metadata, access controls, and privacy-by-design (e.g., fine-grained controls such as Immuta or equivalent).
• Advanced analytics/AI (incl. GenAI where appropriate) for decision support, recommendations, or productivity.